Quantitative trait loci (QTLs) are chromosomal regions containing genes that influence a quantitative (or complex) trait such as peak bone mass. During the last three years of present RO1 funding, we have mapped several QTLs that jointly have a major influence on the attainment of peak bone mineral density in populations derived from C57BL/6 (B6) and DBA/2 (D2) inbred mouse strains. The four largest QTLs (LOD greater than 6) are on chromosomes 1, 2, 4, and 11. Based on mouse-human linkage homology the human counterparts of the four mouse QTLs map of human chromosomes 1q41-43, the pericentromeric region of 11, 1p36 and 5q23-31, respectively. Each of these regions have been identified in recent human genetic studies suggesting that these are highly relevant QTLs, clearly deserving further evaluation. Using congenic strains in which each of these four QTLs have been isolated against a uniform (inbred) genetic background, we propose to continue these studies toward the eventual identification of the gene(s) that underlie each QTL. To accomplish this, we propose to develop small donor segment congenic strains with only a 1-2 cM introgressed segment containing the QTL. We will also begin to examine the interplay among QTLs and other loci in the genome that influence or control QTL expression by conducting a genome- wide search for epistatically-interacting loci. Mouse and human gene databases will be searched to find candidate genes that map within the 1cM introgressed region in each SDS congenic strain. In the case of human databases, this will involve regions of known mouse-human linkage homology. Promising candidate genes that reside within these narrow chromosomal regions will be tested for genotype-dependent expression and/or sequence differences. Using these powerful animal models, we have a high likelihood of isolating putative target genes within each of these four chromosomal regions that participate in the regulation of bone mass. The identification of potential candidate genes would represent a huge step forward in our understanding of skeletal development and should have important implications for the detection of individuals at high risk for osteoporosis.